An improved hybrid ARIMA and support vector machine model for water quality prediction
文献类型：会议论文
| 作者 | Guo, Yishuai1,2; Wang, Guoyin2; Zhang, Xuerui2 ; Deng, Weihui2
|
| 出版日期 | 2014 |
| 会议日期 | October 24, 2014 - October 26, 2014 |
| 会议地点 | Shanghai, China |
| DOI | 10.1007/978-3-319-11740-9_38 |
| 页码 | 411-422 |
| 通讯作者 | Wang, Guoyin |
| 英文摘要 | Traditionally, the hybrid ARIMA and support vector machine model has been often used in time series forecasting. Due to the unique variability of water quality monitoring data, the hybrid model cannot easily give perfect forecasting. Therefore, this paper proposed an improved hybrid methodology that exploits the unique strength in predicting water quality time series problems. Real data sets of water quality provided by the Ministry of Environmental Protection of People’s Republic of China during 2008-2014 were used to examine the forecasting accuracy of proposed model. The results of computational tests are very promising. © Springer International Publishing Switzerland 2014. |
| 会议录 | 9th International Conference on Rough Sets and Knowledge Technology, RSKT 2014
 |
| 语种 | 英语 |
| 电子版国际标准刊号 | 16113349 |
| ISSN号 | 03029743 |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/4759]  |
| 专题 | 大数据挖掘及应用中心 |
| 作者单位 | 1.Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China; 2.Institute of Electronic Information and Technology, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China |
| 推荐引用方式 GB/T 7714 | Guo, Yishuai,Wang, Guoyin,Zhang, Xuerui,et al. An improved hybrid ARIMA and support vector machine model for water quality prediction[C]. 见:. Shanghai, China. October 24, 2014 - October 26, 2014. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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